geodezyx.volc_deform package

Submodules

geodezyx.volc_deform.calc_bl module

geodezyx.volc_deform.calc_bl.baselines_plot(df_bl_inp, col='d_mean0', figax_tup=None, marker='', linestyle='-', suptitle='Direct baselines', ylabel='Distance difference (cm)', plt_shift=0.02, plt_factor=100, decim=100)

Plot baseline distance time series for all site pairs.

Parameters:

  • df_bl_inp (pandas.DataFrame) – DataFrame of baselines as returned by calc_baselines_direct() or calc_baselines_virtual(). Must contain the columns site1, site2, epoch and the column specified by d_col.

  • col (str, optional) – Name of the column to plot on the y-axis. Default is "d_mean0" (centred running mean distance).

  • figax_tup (tuple of (matplotlib.figure.Figure, matplotlib.axes.Axes) or None, optional) – Existing (fig, ax) tuple to draw on. If None a new figure and axes are created. Default is None.

  • marker (str, optional) – Matplotlib marker style passed to ax.plot. Default is "" (no marker).

  • linestyle (str, optional) – Matplotlib line style passed to ax.plot. Default is "-".

  • suptitle (str, optional) – Title string for the figure. Default is "Direct baselines".

Returns:

  • fig (matplotlib.figure.Figure) – The figure object containing the plot.

  • ax (matplotlib.axes.Axes) – The axes object containing the plot.

geodezyx.volc_deform.calc_bl.calc_baselines_direct(df_inp, rovbas_pairs, bases_excluded=[], threshold_mad=3.5, xyz_dic_inp=None, mean_win=86400, strain_win=604800)

Compute direct baselines between rovers and their reference base stations.

Each rover position is differenced from the known (or first-epoch) position of its base station to obtain a baseline displacement time series.

Parameters:

  • df_inp (pandas.DataFrame) – Input DataFrame containing at least the columns rover, base, epoch, x, y, z.

  • rovbas_pairs (list of tuple) – List of (rover, base) pairs to process, e.g. [("ROV1", "BASE1"), ...].

  • bases_excluded (list of str, optional) – Base station names to skip. Default is an empty list.

  • threshold_mad (float, optional) – Median Absolute Deviation multiplier used as the outlier rejection threshold. Default is 3.5.

  • xyz_dic_inp (dict or None, optional) – Dictionary mapping base station name to its reference coordinates {base: [x, y, z]}. If None or the base is not found in the dictionary the first epoch of the rover time series is used as reference. Default is None.

Returns:

df_bls – Concatenated DataFrame of baseline metrics (as returned by _d_calc()) with additional columns:

  • epoch : Observation epoch.

  • site1 : Rover site name.

  • site2 : Base station name.

  • pivot : Always None for direct baselines.

Return type:

pandas.DataFrame

geodezyx.volc_deform.calc_bl.calc_baselines_virtual(df_inp, rov12_pairs, pivots, threshold_mad=3.5, mean_win=86400, strain_win=604800)

Compute virtual baselines between rover pairs via a common pivot station.

For each pivot station the positions of two rovers are differenced to produce a virtual baseline, removing common-mode errors introduced by the pivot.

Parameters:

  • df_inp (pandas.DataFrame) – Input DataFrame containing at least the columns base, rover, epoch, x, y, z.

  • rov12_pairs (list of tuple or list of set) – Rover pairs for which virtual baselines should be computed, e.g. [("ROV1", "ROV2"), ...].

  • pivots (str or list of str) – Name(s) of the pivot (base) station(s) to use.

  • threshold_mad (float, optional) – Median Absolute Deviation multiplier used as the outlier rejection threshold. Default is 3.5.

Returns:

df_bls – Concatenated DataFrame of baseline metrics (as returned by _d_calc()) with additional columns:

  • epoch : Observation epoch.

  • site1 : First rover site name.

  • site2 : Second rover site name.

  • pivot : Pivot station used to derive the virtual baseline.

Return type:

pandas.DataFrame

geodezyx.volc_deform.calc_bl.d_calc(coords_delta, mean_win=86400, strain_win=604800)

Compute baseline distance metrics and strain rate from coordinate differences.

Parameters:

  • coords_delta (array-like of shape (N, 3)) – Array of coordinate differences (dx, dy, dz) for each epoch.

  • mean_win (int, optional) – Rolling window size (in samples) used to compute the running mean of the baseline distance. Default is 86400 (e.g. 1 day at 1 Hz).

  • strain_win (int or list of int, optional) – Window size(s) (in samples) used to compute the strain rate as the relative change of the running mean distance over the window. Default is 7 * 86400 (e.g. 7 days at 1 Hz).

Returns:

df_bl – DataFrame with the following columns:

  • d : Euclidean baseline distance.

  • d0 : Distance centred on its median.

  • d_mean : Rolling mean of the distance.

  • d_mean0 : Rolling mean centred on the overall median.

  • d_diff : First difference of the distance.

  • strainStrain rate computed over the first window in

    strain_win (relative change: (last - first) / first).

  • strain<w>(only when multiple windows are given) Strain rate

    for each additional window size w.

Return type:

pandas.DataFrame

geodezyx.volc_deform.map_stations module